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Proper Orthogonal Decomposition Analysis of the Flow Downstream of a Dysfunctional Bileaflet Mechanical Aortic Valve.

Author(s): Darwish A, Di Labbio G, Saleh W, Kadem L

PURPOSE: Aortic valve replacement remains the only viable solution for symptomatic patients with severe aortic valve stenosis. Despite their improved design and long history of successful operation, bileaflet mechanical heart valves are still associated wit...

Article GUID: 33469847
Experimental Investigation of the Effect of Heart Rate On Flow in the Left Ventricle in Health and Disease -- Aortic Valve Regurgitation.

Author(s): Di Labbio G, Ben-Assa E, Kadem L

J Biomech Eng. 2019 Nov 01;: Authors: Di Labbio G, Ben-Assa E, Kadem L

Article GUID: 31701119
Jet collisions and vortex reversal in the human left ventricle.

Author(s): Di Labbio G, Kadem L

J Biomech. 2018 09 10;78:155-160 Authors: Di Labbio G, Kadem L

Article GUID: 30049450
Response to letter to the editor: 'Left ventricular flow in the presence of aortic regurgitation'.

Author(s): Di Labbio G, Kadem L

J Biomech. 2019 Apr 18;87:212-214 Authors: Di Labbio G, Kadem L PMID: 30871721 [PubMed - in process]

Article GUID: 30871721
Experimental investigation of the flow downstream of a dysfunctional bileaflet mechanical aortic valve.

Author(s): Darwish A, Di Labbio G, Saleh W, Smadi O, Kadem L

Artif Organs. 2019 May 08;: Authors: Darwish A, Di Labbio G, Saleh W, Smadi O, Kadem L

Article GUID: 31066923
Title:Proper Orthogonal Decomposition Analysis of the Flow Downstream of a Dysfunctional Bileaflet Mechanical Aortic Valve.
Authors:Darwish A,  Di Labbio G,  Saleh W,  Kadem L
Link:https://www.ncbi.nlm.nih.gov/pubmed/33469847
DOI:10.1007/s13239-021-00519-w
Category:Cardiovasc Eng Technol
PMID:33469847
Dept Affiliation: ENCS
1 Laboratory of Cardiovascular Fluid Dynamics, Department of Mechanical, Industrial and Aerospace Engineering, Concordia University, 1455 de Maisonneuve Blvd. W, Montréal, QC, H3G 1M8, Canada. lcfd@encs.concordia.ca.
2 Mechanical Engineering Department, Assiut University, Assiut, Egypt. lcfd@encs.concordia.ca.
3 Laboratory of Cardiovascular Fluid Dynamics, Department of Mechanical, Industrial and Aerospace Engineering, Concordia University, 1455 de Maisonneuve Blvd. W, Montréal, QC, H3G 1M8, Canada.
4 Laboratoire de Dynamiques des Fluides, Polytechnique Montréal, Montréal, QC, Canada.
5 Mechanical Engineering Department, Assiut University, Assiut, Egypt.

Description:

Proper Orthogonal Decomposition Analysis of the Flow Downstream of a Dysfunctional Bileaflet Mechanical Aortic Valve.

Cardiovasc Eng Technol. 2021 Jan 19; :

Authors: Darwish A, Di Labbio G, Saleh W, Kadem L

Abstract

PURPOSE: Aortic valve replacement remains the only viable solution for symptomatic patients with severe aortic valve stenosis. Despite their improved design and long history of successful operation, bileaflet mechanical heart valves are still associated with post-operative complications leading to valve dysfunction. Thus, the flow dynamics can be highly disturbed downstream of the dysfunctional valve.

METHODS: In this in vitro study, the flow dynamics downstream of healthy and dysfunctional bileaflet mechanical heart valves have been investigated using particle image velocimetry measurements. Proper orthogonal decomposition of the velocity field has been performed in order to explore the coherent flow features in the ascending aorta in the presence of a dysfunctional bileaflet mechanical heart valve.

RESULTS: The ability of proper orthogonal decomposition derived metrics to differentiate between heathy and dysfunctional cases is reported. Moreover, reduced-order modeling using proper orthogonal decomposition is thoroughly investigated not only for the velocity field but also for higher order flow characteristics such as time average wall shear stress, oscillatory shear index and viscous energy dissipation.

CONCLUSION: Considering these results, proper orthogonal decomposition can provide a rapid binary classifier to evaluate if the bileaflet mechanical valve deviates from its normal operating conditions. Moreover, the study shows that the size of the reduced-order model depends on which flow parameter is required to be reconstructed.

PMID: 33469847 [PubMed - as supplied by publisher]